Triple
T1997849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giraffa camelopardalis |
E43397
|
entity |
| Predicate | averageMassFemale |
P31786
|
FINISHED |
| Object | around 1,200 kilograms |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: around 1,200 kilograms | Statement: [Giraffa camelopardalis, averageMassFemale, around 1,200 kilograms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageMassFemale Context triple: [Giraffa camelopardalis, averageMassFemale, around 1,200 kilograms]
-
A.
averageWeightFemale
chosen
Indicates the typical or mean body weight associated specifically with female individuals within a given group or context.
-
B.
averageWeight
Indicates the typical or mean weight value associated with an entity or group of entities.
-
C.
approximateMass
Indicates that one entity has a mass value that is an estimate or close approximation of the mass of another entity.
-
D.
numberOfFemaleAthletes
Indicates the count of athletes who are female in a given context or group.
-
E.
hasMass_kg
Indicates that an entity possesses a specific mass measured in kilograms.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a88715dbbc8190b2299e29e955d997 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb91055d88190a980e7b42e5895d4 |
completed | March 7, 2026, 5:35 a.m. |
| PD | Predicate disambiguation | batch_69abb79c97d48190b3147430ed39faa9 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:37 p.m.